1) Intentional behavioral-based gestures. Previous gesture studies mostly focused on illustrative (or iconic) gestures [1]}, e.g., waving hands as “hello” or “goodbye”, which are intentionally performed for conveying certain meanings or feelings during interactions. However, in many occasions people would suppress or hide their feelings (especially negative ones) rather than expressing them. Previous studies [2]}, [3]}, [4]} showed that there is a special group of gestures, the micro-gestures (MGs), which are helpful to understand such suppressed or hidden emotions. The major difference between MGs and illustrative gestures is that MGs are unintentional behaviors elicited by people's inner feelings, e.g., rubbing hands due to stress, and the function of MGs is for relieving or protecting oneself from negative feelings rather than presenting for others. Thus, being able to automatically recognize MGs would allow emotion understanding at a better level. To the best of our knowledge, there is no publicly available dataset for this emotional MGs research in the field of computer vision.
